Extend the Life Expectancy of Your Segmentation with Big Data

Editor’s Note: This is the final installment of a three-part series discussing how Big Data can be exploited to enrich market segmentations.

When clients request segmentation research, we often start the discussion by asking if segmentation is really what they need. Included in that discussion is consideration of how long the segmentation is expected to or should live in the organization. For some brands, the answer is short term (one to three years). For others, there is a desire for a solution to live on for five to 10 years, which feels like an eternity. How can this be accomplished, given the pace of change in the world today? As you may have guessed, Big Data has a role to play.

The “Build and Refresh” Approach
British statesman Philip Dormer Stanhope said, “May you live as long as you are fit to live, but no longer.” Now, we are not advocating that Big Data is a segmentation fountain of youth.  As the quote conveys, all things have their time. And no segmentation should live beyond its expiration date. What we are talking about is how Big Data can be applied to a well-designed segmentation to “refresh” the segments over time.

The foundation for segmentation longevity starts at the beginning of the journey—a thoughtfully constructed, robust segmentation whose genesis includes traditional survey data and relevant Big Data streams. This is an important point—you must build into the original segmentation the Big Data streams that will eventually be used to refresh the segments.

Identifying the Big Data streams to use to build and later refresh your segments means considering the population of customers and targets you are interested in. The relevant sources are often the same ones used by target marketers to “find” people for campaigns. Some examples:

  • In the automotive and housing markets, demand and preferences are associated with things like life stage, socio-economic status and geography. The Census is one source of population data that includes these variables. As such, the regular updates published by the Census that capture shifts in population trends by geography can be used to refresh or recalibrate segments over time.
  • Our second post in this series included a discussion of how Big Data could be used in the energy industry to develop and locate targets for energy efficiency programs. The same Big Data that were included in that example (e.g., socio-demographics from the Census, lifestyle preferences from Acxiom, weather data from the NCDC) could be utilized on a longitudinal basis to refresh those segments over time.

When appropriate, taking a “build and refresh approach” to segmentation provides cost savings to the organization and is also culturally kind in that it spares internal stakeholders from mastering a new market view every few years.

Including Big Data in your segmentation development efforts not only adds richness to your original segmentation solution, it also can help extend the life of the core solution when the industry is relatively stable or where the purchase cycle is fairly long. This approach is obviously less applicable in dynamic industries that are rapidly progressing.

We’ve enjoyed providing this three-part series on the practical uses of Big Data for segmentation efforts, and we hope it has sparked ideas for how you can strengthen segmentation efforts for your company.

Please feel free to contact me or Ray Reno if you have questions or would like to discuss how Market Strategies can help you. In the meantime, here are handy links to the first two posts in this series: Use Big Data To Sharpen Your Segmentation and Blend Big Data and Survey Data to Drive Successful CX Programs.

Special thanks to Dr. Raymond Reno for his contributions to this post.

This entry was posted in Energy, Industry Expertise, Research Specialties, Segmentation and tagged , , by Dawn Palace, Ph.D.. Bookmark the permalink.
Dawn Palace, Ph.D.

About Dawn Palace, Ph.D.

Dawn Palace is a senior vice president in the Life Sciences Research division at Market Strategies International. She draws on more than 20 years of experience in market research and integrated marketing to help clients address their needs for business intelligence and transform insights into improvement strategies and marketing campaigns with measurable ROI. Dawn has helped clients create and launch brands, segment markets and deploy CRM programs, develop and launch new products, measure and optimize the customer experience, and improve employee engagement. Dawn received her doctorate and masters’ degrees from Wayne State University and her bachelor’s degree from the University of Michigan. Her passions outside of work include food, wine, volunteer work, and spectating at her children’s sporting events.

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